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Optimisation of galaxy identification methods on large interferometric surveys
The astronomical size of spectral data cubes that will result from the SKA pathfinders planned large HI surveys such as LADUMA; Fornax HI survey; DINGO; WALLABY; etc. necessitate fully automated three-dimensional (3D) source finding and parametrization tools. A fraction of the percentage difference...
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| Format: | Thesis |
| Language: | English |
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Department of Astronomy
2019
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| _version_ | 1867613216794738688 |
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| access_status_str | Open Access |
| author | Gqaza, Themba |
| author2 | Kraan-Korteweg, Renee Christine |
| author_browse | Gqaza, Themba Kraan-Korteweg, Renee Christine |
| author_facet | Kraan-Korteweg, Renee Christine Gqaza, Themba |
| author_sort | Gqaza, Themba |
| collection | Thesis |
| description | The astronomical size of spectral data cubes that will result from the SKA pathfinders planned large HI surveys such as LADUMA; Fornax HI survey; DINGO; WALLABY; etc. necessitate fully automated three-dimensional (3D) source finding and parametrization tools. A fraction of the percentage difference in the performance of these automated tools corresponds to a significant number of galaxies being detected or undetected. Failure or success to resolve satellites around big spirals will affect both the low and the high mass end of the HI mass function. As a result, the performance and efficiency of these automated tools are of great importance, especially in the epoch of big data. Here I present the comprehensive comparison of performance between the fully automated source identification and parametrization software: SOFIA, the visual galaxy identification method and the semi-automated galaxy identification method. Each galaxy identification method has been applied to the same ∼ 35 gigabytes 3D HI data cube. The data cube results from the blind HI imaging survey conducted using the Westerbork Synthesis Radio Telescope (WSRT). The survey mapped the overdensity corresponding to the Perseus-Pisces Supercluster filament crossing the Zone-of-Avoidance (ZoA), at (`, b) ≈ (160◦ , 0.5◦ ). A total of 211 galaxies detected using the semi-automated method by Ramatsoku et al. [2016]. In this work, I detected 194 galaxies (using the visual identification method) of which 89.7% (174) have cross-matches/counterparts on the galaxy catalogue produced through semi-automated identification method. A total of 130 detections were made using SOFIA of which 89 were also identified by the two other methods. I used the sample of 174 visual detections with semi-automated counterparts as a Testbed to calculate the reliability and completeness achieved by SOFIA. The achieved reliability is ∼ 0.68 whereas completeness is ∼ 0.51. Further parameter fine-tuning is necessary to have a better handle on all SOFIA parameters and achieve higher reliability and completeness values. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/30072 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:37.404Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Department of Astronomy |
| publisherStr | Department of Astronomy |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/30072 Optimisation of galaxy identification methods on large interferometric surveys Gqaza, Themba Kraan-Korteweg, Renee Christine Jarrett, Thomas techniques: interferometric-methods: data analysis-radio lines: galaxies The astronomical size of spectral data cubes that will result from the SKA pathfinders planned large HI surveys such as LADUMA; Fornax HI survey; DINGO; WALLABY; etc. necessitate fully automated three-dimensional (3D) source finding and parametrization tools. A fraction of the percentage difference in the performance of these automated tools corresponds to a significant number of galaxies being detected or undetected. Failure or success to resolve satellites around big spirals will affect both the low and the high mass end of the HI mass function. As a result, the performance and efficiency of these automated tools are of great importance, especially in the epoch of big data. Here I present the comprehensive comparison of performance between the fully automated source identification and parametrization software: SOFIA, the visual galaxy identification method and the semi-automated galaxy identification method. Each galaxy identification method has been applied to the same ∼ 35 gigabytes 3D HI data cube. The data cube results from the blind HI imaging survey conducted using the Westerbork Synthesis Radio Telescope (WSRT). The survey mapped the overdensity corresponding to the Perseus-Pisces Supercluster filament crossing the Zone-of-Avoidance (ZoA), at (`, b) ≈ (160◦ , 0.5◦ ). A total of 211 galaxies detected using the semi-automated method by Ramatsoku et al. [2016]. In this work, I detected 194 galaxies (using the visual identification method) of which 89.7% (174) have cross-matches/counterparts on the galaxy catalogue produced through semi-automated identification method. A total of 130 detections were made using SOFIA of which 89 were also identified by the two other methods. I used the sample of 174 visual detections with semi-automated counterparts as a Testbed to calculate the reliability and completeness achieved by SOFIA. The achieved reliability is ∼ 0.68 whereas completeness is ∼ 0.51. Further parameter fine-tuning is necessary to have a better handle on all SOFIA parameters and achieve higher reliability and completeness values. 2019-05-15T07:05:01Z 2019-05-15T07:05:01Z 2018 2019-05-14T11:41:35Z Master Thesis Masters MSc http://hdl.handle.net/11427/30072 eng application/pdf Department of Astronomy Faculty of Science |
| spellingShingle | techniques: interferometric-methods: data analysis-radio lines: galaxies Gqaza, Themba Optimisation of galaxy identification methods on large interferometric surveys |
| thesis_degree_str | Master's |
| title | Optimisation of galaxy identification methods on large interferometric surveys |
| title_full | Optimisation of galaxy identification methods on large interferometric surveys |
| title_fullStr | Optimisation of galaxy identification methods on large interferometric surveys |
| title_full_unstemmed | Optimisation of galaxy identification methods on large interferometric surveys |
| title_short | Optimisation of galaxy identification methods on large interferometric surveys |
| title_sort | optimisation of galaxy identification methods on large interferometric surveys |
| topic | techniques: interferometric-methods: data analysis-radio lines: galaxies |
| url | http://hdl.handle.net/11427/30072 |
| work_keys_str_mv | AT gqazathemba optimisationofgalaxyidentificationmethodsonlargeinterferometricsurveys |